Pipper/finetuned_sol
By Pipper · ↓ 9 · ♥ 0 · Updated 2023-11-21
What's in this repo
This page lists the files in Pipper/finetuned_sol, including decoder_model.onnx, decoder_model_merged.onnx, decoder_model_merged_quantized.onnx and more.
- 6 ONNX models (.onnx files)
- 17 files, including 6 .json, 6 .onnx, 2 .bin, 1 .md, 1 .txt
- Last updated 2023-11-21
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/decoder_model.onnx | — | Download |
| onnx/decoder_model_merged.onnx | — | Download |
| onnx/decoder_model_merged_quantized.onnx | — | Download |
| onnx/decoder_model_quantized.onnx | — | Download |
| onnx/decoder_with_past_model.onnx | — | Download |
| onnx/decoder_with_past_model_quantized.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
finetuned_sol
This model is a fine-tuned version of ckandemir/solidity-generator on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2695
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7e-05
- train_batch_size: 26
- eval_batch_size: 26
- seed: 100
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 104
- total_eval_batch_size: 104
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3698 | 1.0 | 33010 | 0.3371 |
| 0.3292 | 2.0 | 66020 | 0.2977 |
| 0.3067 | 3.0 | 99030 | 0.2782 |
| 0.2956 | 4.0 | 132040 | 0.2695 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3
Model info
Created: 2023-10-30
Updated: 2023-11-21
View on Hugging Face